A Multi-Objective Green Vehicle Routing Problem with Node Functionality Decisions and Location-dependent Demand for the Recycling Waste Sector

Reverse supply chain in the recyclable waste management sector is gaining its momentum through the optimization of routing and emissions. However, the application of reverse supply chain in achieving green objectives is through green vehicle routing problems (GVRP) mainly considering green objectives or constraints. This shows the lack of integrating features in GVRP models in terms of its supply chain network and optimizing decisions in demand and functionality of a location node while considering their relationship. The study developed a multi-objective GVRP model for reverse supply chain in the recyclable waste setting considering location-dependent demand and node functionality decisions with green and economic objectives, where it aims to analyze the routing selection behavior once these features are integrated in the assignment of functionality of nodes. Validation is performed through DICOPT solver in GAMS and insertion heuristic with weighted goal programming to solve the multi-objective model. The study found that the model prefers to route least distances and to open dual functionality nodes for less emissions and routing costs. This gives direction to organizations to prioritize passing more nodes and manner of opening nodes. Further research is to consider multiple periods and level of impact to demand based on different factors.